Abstract
One of the issues that organizations need to address when they intend to launch a data governance program is to know their level of maturity with respect to data governance, data management, and data quality management. By doing so, they will be able to estimate whether they are sufficiently well prepared to address the objectives that have been included in the data governance program.
This chapter introduces some of the most well-known maturity models in the disciplines’ landscape (DAMA, Aiken’s, DMM, IBM, Gartner, DCAM) with special emphasis on the Alarcos’ Model for Data Maturity (MAMD).
MAMD has two fundamental components: a Process Reference Model (based on the recently updated Spanish national specifications UNE 0077, UNE 0078, and UNE 0079) and a Process Assessment Model (recently updated with the publication of the UNE 0080 specification).
Finally, different practical applications of MAMD are presented.
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Notes
- 1.
Executed in collaboration with the Spanish University of Castilla-La Mancha, the Korean University of Myongji, the Spanish companies Lucentia Lab and IE, and the Korean company GTOne. More information at https://alarcos.esi.uclm.es/proyectos/DQIoT/index.php
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Acknowledgments
This work has been partially funded by the ADAGIO project (Alarcos’ DAta Governance framework and systems generatIOn), JCCM Consejería de Educación, Cultura y Deportes, and FEDER funds (SBPLY/21/180501/000061).
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Caballero, I., Gualo, F., Rodríguez, M., Piattini, M. (2023). Maturity Models for Data Governance. In: Caballero, I., Piattini, M. (eds) Data Governance. Springer, Cham. https://doi.org/10.1007/978-3-031-43773-1_7
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